Research And Application Of Logistics Equipment Modeling Design Based On Product Gene Network

Product image design is an important design strategy of current enterprises.The subjectivity and ambiguity of user requirements make it more and more difficult for enterprises and designers to grasp the real user needs.The actual value of design based solely on computer-aided technology is limited.Completely replace the designer.In actual production,there is a problem that the product brand image does not conform to the image style,and the appearance of the product is out of line with user preferences and social aesthetic trends.Therefore,how to scientifically use modern design methods to design product target design,effectively integrate user preference needs and social aesthetic trends,and form a unique brand shape gene of the enterprise to assist designers and enterprises to improve product market competitiveness,which is an important product design.problem.The research objective of this subject is to introduce the concept of product gene network into the design of logistics equipment,establish the logistics equipment modeling gene network model,define the logistics equipment modeling problem as multi-objective optimization problem(MOO),and build a multi-target driven product morphological gene network.The model is applied to the stage of manual optimization design and intelligent optimization design.Finally,the product prototype multi-objective optimization design interactive prototype system is established.It is applied to the logistics equipment modeling design to realize the upgrade iteration of computer-aided logistics equipment design and help designers and enterprises.Improve design efficiency and improve product market competitiveness.First,build a multi-target driven product morphological gene network model(M-FGN).Based on brand image,user preference and social situation,the multi-target driving space is constructed.The design of product morphological gene nodes and edges is analyzed.The product morphological gene is used as the node,and the correlation between nodes is used as the edge to construct M-FGN.Network;topological analysis of the network,analysis of hidden design knowledge is provided to the designer,assisting the designer to manually optimize the design.Taking the logistics equipment AGV side shape design as an example,the logistics equipment case library and product information database were established,and the AGV trolley side shape M-FGN network was drawn.The topology analysis and design knowledge transformation of the network were carried out,and the control experiment was carried out to verify the M-FNG.The visual aid of the network in the artificial optimization design phase.Secondly,a multi-objective evaluation model of product morphology based on RBF neural network is established.Based on the macro-design knowledge extracted from the M-FGN network,the product form coding is simplified,the product shape parameters are used as the input layer,and the target evaluation data is used as the output layer to construct the RBFNN model,thereby realizing the mapping between the product form genes and the target requirements.The multi-objective evaluation model of the side profile of the logistics equipment AGV was established.The validity of the network was verified by the mean square error function and the paired sample t test.Finally,a multi-objective optimization design model and interactive prototype system based on improved MOABC algorithm are established.The node group information extracted by the M-FGN network adopts the population size of the divide-and-conquer strategy-based dimensionality reduction bee colony algorithm,and introduces external archives and elite retention strategies to improve the multi-objective artificial bee colony algorithm.The established RBFNN network model is used as the fitness function of the improved MOABC algorithm,and the product shape multi-objective optimization model is established to achieve the optimal design of the target shape.The Pareto solution set obtained by the algorithm is further screened by the comprehensive evaluation method of multi-method integration,and the final optimization scheme is obtained.Taking the lateral configuration of the logistics equipment AGV as an example,the AGV side shape multi-objective optimization design interactive prototype system is established,the effectiveness of the verification method is valid,and the computer-aided innovation design of logistics equipment modeling is realized.This paper defines the logistics equipment modeling problem as multi-objective optimization problem,and introduces the product gene network concept into the logistics equipment modeling design.The proposed M-FGN network makes the traditional design activity based solely on the designer experience more scientific.It improves the accuracy of the AGV car brand image and the user's perceptual needs,and provides an auxiliary role for designers to explore the hidden design knowledge in the user's emotional image.At the same time,through the introduction of intelligent algorithm,the AGV side shape multi-objective evaluation model and multi-objective optimization design model are established,and the interactive design prototype system is established,which is applied to enterprise product development and realizes the innovative design of logistics equipment.